Adaptive control of stochastic manufacturing systems with hidden Markovian demands and small noise

Adaptive control of stochastic manufacturing systems with hidden Markovian demands and small noise

The adaptive production planning of failure-prone manufacturing systems is considered in this paper. In real manufacturing systems, the product demand is usually not known a priori. One of the major tasks in production scheduling is to estimate and predict the demand. In this paper, the authors consider the demand to be either the sum of an unknown rate and a small white noise or the sum of a h...

An Efficient Algorithm to Inter and Intra-Cell Layout Problems in Cellular Manufacturing Systems with Stochastic Demands

Stochastic Systems with Markovian Switching

Motivated by the study of a class of large-scale stochastic systems with Markovian switching, this correspondence paper is concerned with the practical stability in the pth mean. By investigating Lyapunov-like functions and the basic comparison principle, some criteria are derived for various types of practical stability in the pth mean of nonlinear stochastic systems. The main contribution of ...

Almost sure exponential stability of stochastic reaction diffusion systems with Markovian jump

The stochastic reaction diffusion systems may suffer sudden shocks‎, ‎in order to explain this phenomena‎, ‎we use Markovian jumps to model stochastic reaction diffusion systems‎. ‎In this paper‎, ‎we are interested in almost sure exponential stability of stochastic reaction diffusion systems with Markovian jumps‎. ‎Under some reasonable conditions‎, ‎we show that the trivial solution of stocha...

Markovian Delay Prediction-Based Control of Networked Systems

A new Markov-based method for real time prediction of network transmission time delays is introduced. The method considers a Multi-Layer Perceptron (MLP) neural model for the transmission network, where the number of neurons in the input layer is minimized so that the required calculations are reduced and the method can be implemented in the real-time. For this purpose, the Markov process order...